(this document is updated as the weeks proceed)
- Intro video to Alex Holcombe, find it in Canvas
Week 7: Stats and studies: Correlation and causation
- Correlation and causation intro
- Learning objectives:
- Understand and apply three causal models to explaining correlations
- Know the term “spurious correlation”
- Where does data come from?
- Understanding correlation more deeply
- Three causal models
- X causes Y, Y causes X, a third variable causes both
- Causal model can be at any level of detail
- Explanatory, Outcome, and Nuisance variables
- Recall IV and DV. Bruce slide:

- Nuisance variable
- Is not different, on average, for the different levels of the variable we are interested in
- Confound variables
- Different for the different levels of the variable we are interested in.
- Bruce slide:

- Can you distinguish between confounds and nuisance variables?
- Random assignment
- Bruce slide:

- Randomisation and control group
- Bruce slide

- Time as a third variable
- Relationship between pirates and high average temperature is confounded by time.
- Time: Post hoc ergo propter hoc (After this therefore because of this) fallacy
Week 8
- Dichotomous correlation
- dichotomous variables and correlation
- Contingency tables
- Later you will see the link to arguments and logic
- 4 kinds of control
- Statistical adjustment - controlling for confounds
- A controlled variable - matching
- Causal phrases verus correlational phrases, see “Distinguish correlational and causal..” video on Canvas

Week 9
- Hypothesis testing review and extension
- Review of hypothesis testing (recall tutorial week 5 and Bruce’s 18 March lecture)
- Bruce slide:

- False positives, false negatives, true positives, true negatives
- Hypothesis testing and medical testing
- Sensitivity and specificity
- Why does the news have lots of false positives?
- Excess of statistical comparisons
- More reasons given later in the class, after logic and arguments
Arguments and logic, Weeks 9-10
We’re going to go back and forth between bare-bones examples and arguments from the wild, giving you more and more tools to deal with the real-world ones.
A 9 min intro video on youtube, but it uses different terminology than we use in this unit.
- We need to know good reasons for believing things. Ideally,
- Assumptions are true
- Logic must be airtight (inescapable)
- Syllogisms introduction
- Suppositionally inescapable; inescapable
- Truth contingency tables
- Necessary and sufficient
- Syllogisms
- Suppositionally inescapable, inescapable, suppositionally solid, solid
- Towards real-world arguments
- The vegetarianism argument, student responses, and the difficulty of decoupling
- Redundant premises
- Implicit premises
Arguments and reasoning in the wild, Weeks 11-13
Week 11
- Poly-syllogism
Casting an argument
- Mindset for real-world (4 slides)
- I will happily change, for I seek the truth - Aurelius.
- Most arguments are people just trying to win - to get what they want. Persuasion.
- But ideally you don’t just want to win, you actually want to learn and find things out.
Fallacies.
Weeks 12 and 13
- Deduction and induction in science
- Analysing scientific abstracts